This package provides text and label geometries for ggplot2 that help to avoid overlapping text labels. Labels repel away from each other and away from the data points.

This package provides tools to compute polychoric and polyserial correlations by quick "two-step" methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases.

This package computes Hartigan's dip test statistic for unimodality, multimodality and provides a test with simulation based p-values, where the original public code has been corrected.

This package provides functions to calculate: moments, Pearson's kurtosis, Geary's kurtosis and skewness; it also includes tests related to them (Anscombe-Glynn, D'Agostino, Bonett-Seier).

This package provides a dependency manager for R projects that allows you to manage the R packages your project depends on in an isolated, portable, and reproducible way.

reduceLCS is an implementation of the Reduce-Expand algorithm for LCS. It is a fast program to compute the approximate Longest Commons Subsequence of a set of strings.

Meta-data and tools to work with E. coli. The tools are mostly plotting functions to work with circular genomes. They can used with other genomes/plasmids.

This package provides efficient tools to read and integrate structural variations predicted by popular softwares. Annotation and visulation of structural variations are also implemented in the package.

An unofficial companion to "Applied Logistic Regression" by D.W. Hosmer, S. Lemeshow and R.X. Sturdivant (3rd ed., 2013) containing the dataset used in the book.

Make Bootstrap 4 Shiny dashboards. Use the full power of AdminLTE3', a dashboard template built on top of Bootstrap 4 <https://github.com/ColorlibHQ/AdminLTE>.

This package provides a Bayesian, global planktic foraminifera core top calibration to modern sea-surface temperatures. Includes four calibration models, considering species-specific calibration parameters and seasonality.

Design, workflow and statistical analysis of Cluster Randomised Trials of (health) interventions where there may be spillover between the arms (see <https://thomasasmith.github.io/index.html>).

Changing the name of an existing R package is annoying but common task especially in the early stages of package development. This package (mostly) automates this task.

Model-based clustering of mixed data (i.e. data which consist of continuous, binary, ordinal or nominal variables) using a parsimonious mixture of latent Gaussian variable models.

Scientific and technical article format for the web. Distill articles feature attractive, reader-friendly typography, flexible layout options for visualizations, and full support for footnotes and citations.

Extends ggplot2 functionality to the partykit package. ggparty provides the necessary tools to create clearly structured and highly customizable visualizations for tree-objects of the class party'.

This package provides a collection of datasets for the upcoming book "Graficas versatiles con ggplot: Analisis visuales de datos", by Raymond L. Tremblay and Julian Hernandez-Serano.

Provision of classes and methods for estimating generalized orthogonal GARCH models. This is an alternative approach to CC-GARCH models in the context of multivariate volatility modeling.

This package provides helpers to add Git links to shiny applications, rmarkdown documents, and other HTML based resources. This is most commonly used for GitHub ribbons.

Convert between bookmaker odds and probabilities. Eight different algorithms are available, including basic normalization, Shin's method (Hyun Song Shin, (1992) <doi:10.2307/2234526>), and others.

This package provides tools to access the J-STAGE WebAPI and retrieve information published on J-STAGE <https://www.jstage.jst.go.jp/browse/-char/ja>.

Collections of functions allowing random number generations and estimation of Liouville copulas, as described in Belzile and Neslehova (2017) <doi:10.1016/j.jmva.2017.05.008>.

Non-parametric prediction of survival outcomes for mixture data that incorporates covariates and a landmark time. Details are described in Garcia (2021) <doi:10.1093/biostatistics/kxz052>.

This package provides functions for computing (Mixed and Multiscale) Geographically Weighted Regression with spatial autocorrelation, Geniaux and Martinetti (2017) <doi:10.1016/j.regsciurbeco.2017.04.001>.